Colonoscopy remains the gold-standard screening for colorectal cancer. However, significant miss rates for polyps have been reported, particularly when there are multiple small adenomas. This presents an opportunity to leverage computer-aided systems to support clinicians and reduce the number of polyps missed.In this work we introduce the Focus U-Net, a novel dual attention-gated deep neural network, which combines efficient spatial and channel-based attention into a single Focus Gate module to encourage selective learning of polyp features. The Focus U-Net incorporates several further architectural modifications, including the addition of short-range skip connections and deep supervision. Furthermore, we introduce the Hybrid Focal loss, a new compound loss function based on the Focal loss and Focal Tversky loss, designed to handle class-imbalanced image segmentation. For our experiments, we selected five public datasets containing images of polyps obtained during optical colonoscopy: CVC-ClinicDB, Kvasir-SEG, CVC-ColonDB, ETIS-Larib PolypDB and EndoScene test set. We first perform a series of ablation studies and then evaluate the Focus U-Net on the CVC-ClinicDB and Kvasir-SEG datasets separately, and on a combined dataset of all five public datasets. To evaluate model performance, we use the Dice similarity coefficient (DSC) and Intersection over Union (IoU) metrics.% and 15% improvement over the previous state-of-the-art results of 0.768 and 0.702, respectively.Our model achieves state-of-the-art results for both CVC-ClinicDB and Kvasir-SEG, with a mean DSC of 0.941 and 0.910, respectively. When evaluated on a combination of five public polyp datasets, our model similarly achieves state-of-the-art results with a mean DSC of 0.878 and mean IoU of 0.809, a 14This study shows the potential for deep learning to provide fast and accurate polyp segmentation results for use during colonoscopy. The Focus U-Net may be adapted for future use in newer non-invasive colorectal cancer screening and more broadly to other biomedical image segmentation tasks similarly involving class imbalance and requiring efficiency.  •Automatic polyp segmentation can support clinicians to reduce polyp miss rates.•Focus U-Net combines efficient spatial and channel attention into a Focus Gate.•Focus Gate uses tunable focal parameter to control degree of background suppression.•Deep supervision and new Hybrid Focal loss function further improve performance.•Focus U-Net outperforms state-of-the-art results across five public polyp datasets. However, by pooling across the channel axis, information conveyed by the channels relating to objects features, such as edges and colour, is lost. On the contrary, by assigning weights along the channel axis, channel interdependencies may be explicitly modelled, enabling networks to better recalibrate the features used for segmentation . SqueezeA separate insight incorporated into the Convolutional Block Attention Module (CBAM) for channel attention involves using a global max pooling operation in addition to global average pooling, providing two complementary spatial contexts prior to feature recalibration .The channel module used in the FG is illustrated in 3.4k for the spatial attention module by:Cmax is the maximum channel dimension of the network, C0 is the channel dimension for the first layer, and C is the channel dimension for current layer. The parameters b and γ are set to 2 and 1, respectively . This enables higher values of the focal parameter to significantly reduce the weights of irrelevant regions and features, while salient regions and important features are relatively spared. The effect of altering the focal parameter is illustrated in The concept of a focal parameter originates from work on loss function optimisation, where the contributions of easy examples are downweighed enabling the learning of harder examples ,55. HereCareful tuning of the focal parameter is required, to suppress background regions while preserving attention for borders between foreground and background where attention coefficients take middle values.3.6The vanishing and exploding gradients problems are well-recognised issues with training deep CNNs ,57. The w to different output layers according to Eq. In contrast, deep supervision encourages semantic discrimination of intermediate feature maps at each level by assigning a loss to outputs at multiple layers ,61. EquaIntuitively, higher weights are therefore assigned to the layers requiring a smaller degree of upsampling, with the greatest weight assigned to the final output, followed by an exponential decrease in weighting with increasing depth of the network.3.7y refers to the ground truth label.The training of neural networks is based on solving the optimisation problem defined by the loss function. For semantic segmentation tasks, a popular choice of loss function is the sum of the Dice similarity coefficient (DSC) loss and cross entropy (CE) loss:pi0 is the probability of pixel i belonging to the foreground class and pi1 is the probability of pixel belonging to background class; gi0 is 1 for foreground and 0 for background and conversely gi1 takes values of 1 for background and 0 for foreground.However, with class imbalanced tasks such as polyp segmentation, the resulting segmentation using the Dice loss often leads to high precision but low recall rate . By weigα controls the class weights.Complementary to weighting the positive and negative examples, applying focal parameters to both the Tversky and cross entropy loss enables the downweighting of background objects in favour of foreground object segmentation, and produces the Focal Tversky loss and Focal loss, respectively ,55:(9)LFFinally, we define the Hybrid Focal loss (HFL) as the sum of the Focal Tversky loss and Focal loss:To mitigate suppression of the loss near convergence, we supervise the last layer without the focal parameters .44.1We assess the ability of the Focus U-Net to accurately segment polyps using five public datasets containing images of polyps taken during optical colonoscopy: CVC-ClinicDB , Kvasir-The CVC-ClinicDB database consists of 612 frames containing polyps with image resolution 288 × 368 pixels, generated from 23 video sequences from 13 different patients using standard optical colonoscopy interventions. The Kvasir-SEG database consists of 1000 polyp images collected and verified by experienced gastroenterologists. Images vary in size from 332 × 487 to 1920 × 1072 pixels. CVC-ColonDB consists of 300 images of resolution 500 × 574 pixels obtained from 15 video sequences with a random sample of 20 frames per sequence. ETIS-Larib PolypDB similarly consists of 300 images, with image resolution 1225 × 966 pixels. Lastly, CVC-T consists of 182 frames containing polyps from 8 patients derived from either the CVC-ClinicDB and CVC-ColonDB datasets, with image resolutions of 288 × 384 or 500 × 574 pixels.4.2For our experiments, we use the Medical Imaging Segmentation with Convolutional Neural Networks (MIScnn) open-source Python library . For allγ ∈ [μ = 0.99). We set the initial learning rate at 0.01, and follow a polynomial learning decay rate schedule [For the ablation studies, we use the CVC-ClinicDB dataset, with five-fold cross validation using random assignment. We evaluate the baseline performance of the U-Net  and Atteγ ∈ ,3. Modelschedule :(12)1−epFor fairer comparison, we do not apply any data augmentation techniques at this stage.In contrast, when attempting for state-of-the-art results on the CVC-ClinicDB dataset, we train our final model using five-fold cross validation for 500 epochs and use the following data augmentation techniques: scaling, rotation, elastic deformation, mirror and gamma transformations. For both evaluation on the Kvasir-SEG dataset and evaluation on the combination of all five public datasets, we follow the single train-test split used in Refs. ,31, and α = 0.3 and β = 0.7 for the Tversky index, α = 0.25, γ = 2 for the Focal loss and α = 0.3, β = 0.7 and γ = 3/4 for the Focal Tversky loss [For the Hybrid Focal loss, we follow the optimal hyperparameters reported in the original studies. We set sky loss ,55,62.https://github.com/mlyg/Focus-U-Net.For all cases, the validation loss is evaluated at the end of each epoch, and the model with the lowest validation loss is selected as the final model. All experiments are programmed using Keras with TensorFlow backend and trained with NVIDIA P100 GPUs, with CUDA version 10.2 and cuDNN version 7.6.5. Source code is available at: 4.3To assess segmentation accuracy, we follow recommendations from Ref. , and useThe IoU metric penalises single instances of poor pixel classification more heavily than DSC, providing similar but complementary perspectives on assessing segmentation accuracy. We further assess recall and precision:In the context of polyp segmentation, recall, also known as sensitivity, measures the proportion of the pixels corresponding to the polyp that are correctly identified. In contrast, precision, also known as the positive predictive value, measures the proportion of pixels correctly labelled as representing the polyp. While both are accounted for in the DSC metric, measuring recall and precision provides additional information regarding the false positive and false negative rates.Finally, we evaluate model efficiency by calculating the frames per second (FPS) using the mean inference time:5We first perform a series of ablation studies to evaluate individual components of the Focus U-Net, followed by separate evaluations on the CVC-ClinicDB and Kvasir-SEG datasets, and finally evaluate against a test set combining five public polyp datasets.The results from the ablation study are shown in Performance gains are observed with successive addition of each component, and with all components present there is a significant improvement with a DSC score of 0.875 ± 0.016 compared to the U-Net (0.828 ± 0.021) and Attention U-Net (0.801 ± 0.019). The Focus U-Net achieves similar FPS performance to the Attention U-Net and comparable FPS performance to the U-Net, justifying the improvement in accuracy with minimal efficiency losses.The results for the CVC-ClinicDB dataset are shown in The Focus U-Net achieves state-of-the-art results with a mDSC score of 0.941 and a mIoU score of 0.893, outperforming the ResUNet++ with Conditional Random Field (CRF) and DoubleU-Net. Focus U-Net also has the best recall-precision balance, while PolypSegNet achieves the highest precision at the cost of recall, and conversely the ResUNet++ with CRF achieves high recall at the cost of precision.Next, we evaluate our model on the Kvasir-SEG dataset. The results are shown in Finally, % increase in mDSC over the previous state-of-the-art  and 15% increase in mIoU . The greatest improvements are observed in the most challenging datasets, namely the CVC-ColonDB and ETIS-LaribPolypDB datasets. For CVC-ColonDB, a 20% increase in mDSC is observed over the previous state-of-the-art  and an 87% increase in mDSC compared to the previously top performing Selective Feature Aggregation (SFA) model. Even more significantly, for ETIS-LaribPolypDB, a 23% increase in mDSC is observed over the previous state-of-the-art  and a 180% increase in mDSC compared to SFA.The Focus U-Net achieves the highest score across four of the five datasets with a mDSC of 0.938 and mIoU of 0.889 on the CVC-ClinicDB, mDSC of 0.878 and mIoU of 0.804 for CVC-ColonDB, mDSC of 0.832 and mIoU of 0.757 for ETIS-LaribPolypDB, mDSC of 0.920 and mIoU of 0.860 for CVC-T and mDSC of 0.910 and mIoU of 0.853 for the Kvasir-SEG dataset. Importantly, the combined score takes into account the relative number of images of each dataset, and the Focus U-Net achieves a mDSC of 0.878 and mIoU of 0.702, a 14Examples of polyp segmentations for the five datasets are shown in The accuracy of segmentations obtained from the intermediate layer highlights the ability for the deepest layers to localise the polyp effectively. The Focus U-Net generalises well with consistently accurate segmentations across all datasets. For the images corresponding to the poorest segmentation quality, these are either objectively challenging polyps to identify, or in many cases poor-quality images such as in the CVC-ColonDB example.6In this paper, we introduce a novel dual attention-gated U-Net architecture, named the Focus U-Net, which uses a Focus Gate to encourage learning of salient regions combined with a focal parameter controlling suppression of irrelevant background regions. Moreover, with the additions of short-range skip connections and deep supervision, as well as optimisation based on the Hybrid Focal loss, the Focus U-Net outperforms the state-of-the-art results across five public polyp datasets. Importantly, the proposed architecture performs consistently well across all datasets, demonstrating an ability to generalise to unseen data from different datasets. Visualising the resulting polyp segmentations confirms the segmentation quality, with poorer segmentations associated with a combination of either poorer image quality or objectively more challenging polyps to identify.% and 15% improvement over the previous state-of-the-art results from HarDNet-MSEG with a mDSC of 0.768 and mIoU of 0.702, respectively.The proposed Focus U-Net is the latest addition to lightweight, yet accurate, polyp segmentation models, achieving state-of-the-art results with a mDSC of 0.878 and mIoU score of 0.809 when evaluated on the combination of five public datasets, a 14% reported for small adenomas [While these results are promising, it is important to determine whether such a model may be applied in clinical practice. Given that colonoscopy involves recordings of live video, a model with a fast inference time is required to process images in real-time. Accordingly, the Focus U-Net architecture is efficiently designed, with both efficient channel and spatial attention mechanisms, as well as a lightweight U-Net backbone, with comparable FPS performance to the standard U-Net . With poadenomas , the priThere are several limitations associated with our current study. Firstly, the datasets used to train our model consist of images all containing polyps, in contrast to in practice, where the majority of live video data would not contain a polyp. However, in terms of model training, it has been observed that training with images in the absence of polyps results in poorer generalisation . In termWhile colonoscopy remains the gold-standard for investigating suspected CRC, CT virtual colonography is a relatively newer method for bowel cancer screening that offers non-invasive visualisation of the colon . The fleAll authors in this paper do not have any conflict of interest.


Staphylococcus aureus isolates. The UA-Ch-NPs were synthesized by a simple method and then characterized by TEM, FTIR, DLS-zeta potential, and XRD analyses. According to the characterization results, highly dispersed spherical nanoparticles with a mean diameter of 258 nm and a zeta potential of + 40.1 mV were developed. The antibacterial properties of UA-Ch-NPs were investigated and their inhibitory effect on biofilm formation was demonstrated by AFM. Finally, the expression levels of icaA and icaD were measured using real-time PCR. Results indicated that the minimum inhibitory concentration (MIC) of UA and UA-Ch-NPs against S. aureus was 64 and 32 µg/mL, respectively. The treatment of bacterial cells with UA-Ch-NPs significantly decreased the expression of icaA and icaD genes which are engaged in biofilm formation. Our results indicated that UA-Ch-NPs could be a promising material for antibacterial and antibiofilm applications.  The present study aimed to synthesize ursolic acid-loaded chitosan nanoparticles (UA-Ch-NPs) as an antiinfective agent against 21  Staphylococcus aureus as a Gram-positive bacterium causes several infections including nosocomial infections. S. aureus infections have been shown to be highly variable. For instance, S. aureus causes acute diseases, like bacteremia and severe chronic infections [1]. In recent years, S. aureus has represented a serious challenge because of its ability for developing resistance against currently available antibiotics. This resistance is generally linked to the capability of the bacteria to form biofilm. S. aureus strains that are isolated from mastitis in ruminants, for example, produce slime in vivo, resulting in a remarkably higher capacity of colonization in comparison with nonslime producing variants. As a result of biofilm formation in mastitis isolates, susceptibility to antibiotics is reduced, which is the consequence of the reduced antibiotic diffusion through the biofilm matrix and a reduction of the metabolic activity of bacteria inside the biofilm [2]. Thus, a new generation of antibacterial agents is urgently needed to fight S. aureus.E. coli and S. aureus . UA has been indicated to have various effects on some microorganisms, characterizing it as an antibiotic drug. Kozai et al. [5] demonstrated that UA managed to inhibit insoluble glucan synthesis in Streptococcus mutans. Moreover, UA has been shown to fight against S. sobrinus and S. mutans, with a minimum inhibitory concentration (MIC) of 2.0 μg/mL [6]. Furthermore, the antibacterial properties of UA have been discovered on other human bacterial pathogens, including S. pneumonia, methicillin-sensitive, and methicillin-resistant Bacillus cereus, Staphylococcus aureus, and Pseudomonas aeruginosa [7]. Ursolic acid  as a natural pentacyclic triterpenoid carboxylic acid is found in various plants. This agent is highly potential to provide defense against certain pathogens such as Despite its ability to kill bacteria, UA has low water solubility which limits its clinical applications. Therefore, different methods were proposed for improving UA antibacterial activity. Some nano-drug delivery systems have been used for increasing drug solubility . In this regard, some natural water-soluble polymers, like alginate, chitosan, or poly(lactic-co-glycolic acid) have been widely employed in drug delivery systems owing to their biodegradability and biocompatibility features [10–13]. S. aureus. It was assumed that UA-Ch-NPs could overcome the solubility of UA and improve its efficacy. The biological applications, such as growth-inhibitory effects and biofilm formation prevention activity of this agent were evaluated as well.Chitosan (Ch) is a natural polysaccharide polymer; it is a deacetylated chitin derivative. Thanks to its low toxicity and high biocompatibility, this biological material has been widely used in many biomedical applications . Ch has potency for drug delivery through the paracellular pathway. Jin et al. [10] loaded UA in Ch nanoparticles to study their antiangiogenesis activity in tumors through in vitro and in vivo investigations. Although synthesis of UA-loaded Ch nanoparticles and their antitumor properties have been reported, to the best of authors’ knowledge, there is no study concentrating on the antiinfective properties of the UA-loaded Ch nanoparticles. Therefore, this study aims to investigate the antiinfective properties of ursolic acid-loaded chitosan nanoparticles (UA-Ch-NPs) against n = 1600 determined by the supplier) and ursolic acid (98.6%) were purchased from Sigma-Aldrich Co., Germany. Ethyl-(3-3-dimethylaminopropyl) and N-hydroxy-succinimide (NHS) were purchased from Beyotime Institute of Biotechnology, China. S. aureus ATCC 25923 was supplied by Pasteur Institute, Iran. Penicillin and Ciprofloxacin were obtained from Jaber Ebne Hayyan Pharmaceutical Co., Iran. Ceftiofur, erythromycin, tetracycline, trimethoprim, ampicillin, chloramphenicol, and gentamicin were obtained from Pharmacia & Upjohn, Belgium.Chitosan , and 8 mg N-hydroxysuccinimide (NHS) were mixed with the obtained solution. It was then vortexed overnight at ambient temperature. Then, the sample was centrifuged for 20 min at 11,000 rpm. The harvested pellets were UA-Ch-NPs that were lyophilized for prolonged storage.To confirm the successful production of UA-Ch-NPs, Fourier transform infrared (FTIR) analysis was conducted using a FTIR spectrophotometer (Perkin Elmer Spectrum RXI). This experiment was carried out for UA, Ch, and UA-Ch-NPs samples. Transmission electron microscopy  was used to study the morphology of the prepared samples and Digimizer image analysis software (version 5.3.4) was used to measure the mean size of the nanoparticles. The X-ray diffraction (XRD) analysis was also performed using an INEL Equinox 3000 diffractometer with the CuKα (λ = 1.5406 Å) radiation. The size and surface charge of the produced UA-Ch-NPs were analyzed using DLS-zeta potential analyzer . The surface zeta potential of UA-Ch-NPs was calculated using a dynamic light scattering (DLS) instrument (Brookhaven 90 Plus/BI-MAS). S. aureus ATCC 25923 was purchased from Pasteur Institute of Iran. A total of 21 S. aureus isolates obtained from bovine mastitis were used in this study; the isolation was carried out in the pharmaceutical laboratory, Shahid Beheshti University of Medical Sciences, Tehran, Iran. The disc diffusion approach was used to carry out antibiotic sensitivity testing (AST) against ceftiofur, erythromycin, tetracycline, trimethoprim, penicillin, ampicillin, chloramphenicol, gentamicin, and ciprofloxacin. Firstly, inoculation of the Mueller–Hinton agar Petri dishes with half-McFarland of bacteria was done, followed by the placement of antibiotic discs right onto the agar. The diameters around the discs were determined after 24 h of incubation. The sensitivity to UA-Ch-NPs was assessed based on the inhibition zone diameter, based on the Clinical and Laboratory Standards Institute (CLSI) protocol [16].The MIC value of all pharmaceutical agents was measured by microdilution assay in 96-well plates. Accordingly, 100 µL of sterilized Mueller–Hinton broth (MHB) was added to each well, followed by treating each well separately with serial dilutions of UA and UA-Ch-NPs. The microbial cultures were then adjusted to the turbidity of a 0.5 McFarland standard. The 0.2 mg/mL p-iodonitrotetrazolium chloride (INT) was mixed with each sample. Finally, following incubation at 37 °C for 24 h, the lowest concentration before the color change was determined as the MIC value. 600). The bacteria adhesion to the oil phase was quantified through calculation of the ratio between the optical density prior to and after mixing. Finally, the hydrophobicity degree was categorized into three classes: > 70%, 30%–70%, and < 30% for strong, moderate, and low hydrophobicity, respectively. The bacterial adhesion to hydrocarbons test was used for measuring the relative hydrophobicity of various bacterial strains following the work by Subbiahdoss et al. [17]. In short, bacterial suspension was mixed with n-decane (hydrocarbon phase) at a 1:1.2 ratio, followed by vortexing for 2 h. After the separation of the obtained emulsion, the optical density of the aqueous phase was measured at 600 nm  supplemented with 1% glucose and then seeded into 96-well flat-bottom sterile polystyrene microplate. The broth without bacteria and the inoculated broth without the nanoparticles were considered as negative and positive controls, respectively. The samples were incubated at 37 °C for 24 h. Biofilm stains and the culture medium were removed and washed with phosphate buffered saline (PBS). Afterward, 100 μL gentian violet, 1%, was added and incubated at room temperature for 5 min. The samples were then washed with distilled water to wipe up the excess gentian violet. Eventually, 200 μL glacial acetic acid (33% (w/v)) was added to each well. After 20 min, the ELISA reader  was used to read the absorbance of each sample at 640 nm [18]. 640 values were employed for comparative analysis and semi-quantitative classification of the biofilms produced by the bacterial strains based on the approach presented by Stepanovic et al. [19]. Briefly, the cut-off OD (ODc) was set as three standard deviations above the mean OD of the negative control, and classification of strains was as follows: OD > 4 × ODc = strong biofilm producer; 2 × ODc < OD < 4 × ODc = moderate biofilm producer; ODc < OD < 2 × ODc = weak biofilm producer; and OD < ODc = poor biofilm producer.The OD2. The silicon nitride tips used in the measurements were irradiated with UV for 15 min in the air to remove any organic contaminants. The tip curvature radius was less than 10 nm. The force constant and oscillation frequency were 0.03 N/m and 255 kHz, respectively.Atomic force microscopy  was used to study the biofilm formation in a contact mode of 10 × 10 µm620 values of bacterial cultures were measured at 15 min intervals for 24 h and each one was read 3 times. OD measurements for the development of bacterial growth curves were performed by determining the absorbance at a wavelength of 620 nm. Bacteria were cultured in Costar 96-well flat-bottom plate and treated with different concentrations of UA and UA-Ch-NPs . The ODS. aureus using commercial RNA extraction kits  according to manufacturer instructions. The equal quantity of RNA extracted from each group of bacteria was treated by 5 μL of DNase 1  for the probable presence of contaminating DNA. The RNA samples were then checked for the 16S rRNA gene as an internal standard using below 16S primers. According to the manufacturing protocol , total RNA (2 μg) was used for cDNA synthesis. The reaction was carried out under the following conditions: one cycle at 37 °C for 15 min for reverse transcription, 94 °C for 30 s for the inactivation of enzymes up to 10 μL, and without hot commencement [20]. The RT-qPCR reactions were performed using SYBR Green PCR Master Mix  and ABI 7000 instrument . The used primers were as follows: icaA Forward; 5-ACA CTT GCT GGC GCA GTC AA-3, icaA Reverse; 5-TCT GGA ACC AAC ATC CAA CA-3, icaD Forward; 5-ATG GTC AAG CCC AGA CAG AG-3, icaD Reverse; 5-TGA ACT TAT TCC ACC GCC TTT A-3, Bap Forward; 5- ATA CTG ATG GCG ATG GTA-3, Bap Reverse; 5-ACT GTG TCT TCT GTT GTA AT-3, 16S forward; 5-ACT GGG ATA ACT TCG GGA AA-3 and 16s reverse; 5-CGT TGC CTT GGT AAG CC-3. The PCR mixture’s final volume was 25 μL with 12.5 μL of the master mix, 1 μL each of forward primer and reverse primer, 1 μL of cDNA, and 9.5 μL of free water. The cycling conditions were: 1 cycle at 95 °C for 10 min, and then 40 cycles at 95 °C for 20 s, and 60 °C for 40 s. Finally, to draw the melting curve, the samples were incubated at 95 °C for 15 s, 60 °C for 30 s, and 95 °C for 15 s.Total RNA was extracted from treated and untreated One-way ANOVA was used for the statistical analysis of the experimental data, and results were presented as means ± SD. Also, p < 0.05 was considered statistically significant to verify the variations in the results due to the effect of different treatments. –1 is observed, which is identified as the O–H stretching vibration. The peak at 2940 cm–1 corresponds to the C-H stretching vibrations in methylene groups. The bands at 1720, 1380, 1463, and 1090 cm–1 are related to the C=O stretching vibrations in the carboxylic acid group, C-H groups, C=C stretching vibrations, and C-O stretching vibrations in secondary alcohols, respectively [21]. Ch also showed some characteristic peaks in the FTIR analysis. The presence of O-H, N-H, and intramolecular hydrogen bonds in Ch was confirmed by stretching vibrations around 3200–3600 cm–1. The peaks at 2920 and 2870 cm–1 are related to symmetric and asymmetric stretching vibrations of C-H groups, respectively. The bands at 1650, 1590, and 1350 cm–1 are associated with the C=O stretching vibrations in type I amide, the N-H bending vibrations in type II amide, and the C-N stretching vibrations in type III amide, respectively. The peaks at 1450 and 1360 cm–1 are attributed to the C-H bending and symmetrical vibrations in CH2 and CH3. The absorption bands at 1150 and 1000 cm–1 are related to asymmetric vibrations of C-O-C bridges and C-O stretches, respectively . The changes in the intensity of these peaks and the formation of new peaks in the FTIR spectrum of UA-Ch-NPs suggest the functional interaction between UA and Ch. Two small peaks at 1600 and 1700 cm–1 in the spectrum of UA-Ch-NPs are related to the stretching vibrations of C=O and C-N carbonyl groups associated with the formation of an amide bond between carboxylic acid, ursolic acid, and chitosan amine [22]. The peak at 1550 cm–1 is attributed to the N-H bending vibrations and the wide peak around 3400 cm–1 is related to the O-H stretching vibrations at the Ch surface. The emergence of these peaks in the spectrum of UA-Ch-NPs and the absence of the characteristic peaks of UA confirm the binding interaction between Ch and UA through the formation of amide bonds.The TEM image of the synthesized UA-Ch-NPs is shown in Figure 1a. As shown, spherical nanoparticles with an almost uniform particle size of 75 nm were obtained. The FTIR spectra of UA, Ch, and UA-Ch-NPs are presented in Figure 1b. A unique characteristic peak in the FTIR spectrum of UA at 3520 cmThe results of DLS and zeta potential analysis of UA-Ch-NPs are presented in Figure 1c. Accordingly, the average particle size of UA-Ch-NPs is 258 nm, and its polydispersity index (PDI) is 0.409. Based on the results, the zeta potential of UA-Ch-NPs is +40.1 mV, which is associated with positively charged amine groups on the Ch surface. The XRD patterns of UA and UA-Ch-NPs are shown in Figure 1d. The characteristics peaks associated with UA were observed at 2θ values of 5.15, 8.81, 10.30, 14.50, 16.43, 21.40, and 27.22. These characteristic peaks were also observed in the diffraction pattern of the UA-Ch-NPs indicating the loading of UA on Ch nanoparticles. Ch usually shows a broad diffraction peak at 2θ = 22.6 ° which is also seen in the UA-Ch-NPs diffraction along with some peaks related to UA. The presence of similar characteristic peaks related to UA and UA-Ch-NPs was reported in a previous research [24].S. aureus strains, isolated from bovine mastitis, showed different levels of antimicrobial susceptibility patterns. The antimicrobial resistance (AMR) of S. aureus isolates is shown in Figure 2a. Generally, the high resistance or low susceptibility to antibiotics was observed with penicillin and ciprofloxacin where 66.2% and 76.2% of the isolates were resistant, respectively. Gentamicin revealed the most effective antibiotic effect, and all the S. aureus strains were sensitive to this antibiotic (100% sensitive). The MIC value for UA and UA-Ch-NPs were 64 and 32 µg/mL, respectively , revealing that the growth-inhibitory effects of UA-Ch-NPs were more than those of UA. Results also showed that S. aureus was sensitive to UA and UA-Ch-NPs at MIC, 0.5 MIC, and 2 MIC concentrations . Antibiotic sensitivity of 21  S. aureus, 21 strains isolated from bovine mastitis were cultured. As determined by microtiter plate assay (OD640), among the 21 isolates, biofilm-producing bacteria were classified as moderate (5 isolates) and strong (16 isolates). After 24 h of incubation of the bacteria with UA and UA-Ch-NPs, biofilm formation reduced drastically . A number of studies have indicated a potential effect of bacterial hydrophobicity on bacterial adhesion to host tissues and biofilm formation. Therefore, cell surface hydrophobicity (CSH) and biofilm formation are significantly correlated . Three types of hydrophobicity were identified: weak , moderate (> 30%–70%), and strong (> 70%). In this study, among the 21 isolates of bacterial strains, 62% had strong CSH, and the rest exhibited moderate hydrophobicity. As summarized in Table, among the S. aureus isolates, most strains were strongly hydrophobic. To further study the antibiofilm characteristics of UA-Ch-NPs, AFM analysis was used for the investigation of the interaction between the bacterial cells and the nanoparticles. AFM images of S. aureus showed a significant difference between biofilm formation of the control sample (S. aureus without treatment) and UA-Ch-NPs treatment . Several research studies showed that the icaD and icaA genes of S. aureus have a key role in the synthesis of polysaccharide intercellular adhesion from poly-N-acetylglucosamine contributing to biofilm formation [26]. Our data also showed that UA-Ch-NPs led to a dramatic reduction in both icaA and icaD genes . The statistical analysis showed that the results were statistically significant (p < 0.05).To determine the effects of UA and UA-Ch-NPs on biofilm formation byIn the present study, UA-Ch-NPs were synthesized, and their antiinfective properties were investigated. Several analytical techniques were used to characterize the developed UA-containing nanoparticles to evaluate their suitability for the intended purpose. The TEM analysis showed that the synthesized UA-Ch-NPs had a good monodispersity with spherical morphology. The XRD analysis results confirmed the presence of UA on the Ch nanoparticles and from the FTIR results, the successful interaction of UA with the Ch nanoparticles surface was deduced. The DLS analysis of UA-Ch-NPs showed an average particle size of around 258 nm with a PDI of 0.409. The PDI is a value between 0 and 1. The closer this value is to zero, the greater is the uniformity of the particle size. The best value is around 0 to 0.2 for polymeric nanoparticles; for drug release purposes, this index should be below 0.4, and for other purposes, up to 0.7 is acceptable and shows the uniformity of the particle size [27]. Accordingly, the developed nanoparticles with a PDI of around 0.41 were suitable for the drug delivery purpose. The hydrodynamic diameter obtained from the DLS analysis was 258 nm, which was different from that obtained from the TEM analysis in a dry state (vacuum). This difference in particle size between DLS (258 nm) and TEM (75 nm) is attributed to the positive zeta potential of these nanoparticles that are strongly covered by the water molecules while being dispersed in aqueous solution for DLS analysis and show a large hydrodynamic diameter compared to that obtained from TEM analysis in dry state. The obtained diameter for the synthesized UA-Ch-NPs in this study is in the middle range compared to the other studies on UA-loaded nanocarriers. For instance, an average particle size of 330 nm was reported for UA-loaded Ch/poly (lactic acid) (PLA) nanoparticles [28], while another study reported a particle size of around 100–200 nm (an average of 120 nm) for UA-loaded Ch nanoparticles [10]. There is not a consensus among researchers about the suitable particle size to be absorbed by the intestinal mucosa. Some investigations have reported that particles with the size 130–950 nm are suitable to be absorbed by intestinal M cells [29]. The oversized pores of tumor microvessels varies from 100–1200 nm [30], hence, nanoparticles with a size of about 250 nm size could enter the broad fenestrations of the tumor tissues, while they are not able to enter the vessels of the normal endothelium which are narrow, approximately 5–10 nm [23]. Hence, the particle size obtained in this study has a relatively suitable size for drug delivery applications.The zeta potential of the prepared nanoparticles was +40.1 mV demonstrating their high stability and the positive charge of the particles, which provide an effective system for drug delivery due to being taken up by proliferating cells. This effect was confirmed by previous studies [31]. The binding of nanoparticles to the cell membrane is affected by the charge of the NPs. Since cellular surfaces are dominated by negatively charged sulphated proteoglycans molecules that are highly anionic, the interaction between the proteoglycan and the nanoparticle shell (positively charged) is ionic, so the higher surface charge of the nanoparticles results in a stronger attachment of the nanoparticles to the cell membrane and higher adsorption of the nanoparticles [32]. Antonio et al. [28] also reported that by the incorporation of Ch to the surface of UA-loaded PLA nanoparticles, the zeta potential increased from –25 to +28 mV because of the amino groups of the Ch molecules, which facilitated the interaction of the nanoparticles with biological membranes.S. aureus and its biofilm formation ability were observed. While S. aureus was resistant to antibiotics, it showed high susceptibility to UA and UA-Ch-NPs. In a study by Wu et al. [33], the stable antibacterial effect of triterpene derivatives such as UA was also demonstrated. In addition, the reduction of the MIC value for UA-Ch-NPs compared to UA is an indication of the higher growth-inhibitory effects of UA-Ch-NPs, which is confidently associated with the presence of Ch. It has been reported that Ch derivatives can interact with microbial cell membranes and ultimately decrease membrane integrity [34]. Qi et al. [35] also reported that Ch-NPs act against S. aureus by inhibiting their growth through membrane disruption and leakage of metabolites.In vitro studies demonstrated the antiinfection activity induced by UA-Ch-NPs. The antimicrobial effects of UA-Ch-NPs on the growth of S. aureus infection. Our findings also indicated that UA-Ch-NPs were able to inhibit bacterial growth in a concentration-dependent manner. According to Figure 2c, the developed UA-Ch-NPs prolonged the lag phase of S. aureus and also reduced the OD. Generally, during the lag phase, cells are depleted of metabolites and enzymes because they are adapting to their new growth conditions. In this phase, intermediates, enzymes, RNA, and other molecules are made to resume the growth. In this situation, the occurrence of a long lag phase is probable, which represents the period required for sufficient multiplication of a few mutants in the inoculum for an apparent rise in cell number [36]. This study mainly aimed to produce a nanoformulation to combat S. aureus isolates. Emerging data is trying to characterize genes engaged in biofilm formation. For example, the icaA and icaD genes have been extremely characterized before being engaged in S. aureus biofilm formation [36]. These genes contribute to the intercellular attachment of bacteria and biofilm formation. Our data also clearly indicated that the treatment of bacterial cells with UA-Ch-NPs significantly reduced icaA and icaD, and consequently, biofilm formation. Qian et al. [37] also reported that UA disrupted the cell membrane integrity of carbapenem-resistant Klebsiella pneumoniae, and strong inhibitory influences against the expression of biofilm-related genes and biofilm formation were reported.In addition, our findings also showed that UA-Ch-NPs reduced the biofilm formation by the S. aureus revealed the enhanced inhibitory effect of the UA-loaded nanoparticles due to the presence of Ch nanoparticles. This pharmaceutical agent reduced the growth of S. aureus and its biofilm formation, which was also confirmed by the AFM analysis. The treatment of bacterial cells with UA-Ch-NPs significantly decreased the expression of icaA and icaD genes which are engaged in biofilm formation. The results of this study indicated that UA-Ch-NPs could serve as an antibiotic agent, however, this needs to be confirmed by further research in the future. The current study managed to produce UA-Ch-NPs successfully. According to the TEM analysis, the synthesized nanoparticles were uniform in size with a good monodispersity. Moreover, the FTIR analysis results showed the interaction between functional groups of UA and Ch and thereby the successful loading of UA on the nanoparticles. The XRD results also showed the characteristic peaks associated with UA in UA-Ch-NPs. According to the results, a decrease in the MIC value of UA-Ch-NPs in comparison with UA against


To date, no strong clinical HT predictors present at diagnosis have yet been identified. The fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) is highlighted as a non-invasive diagnostic tool for the detection of HT, but its ability to predict HT at early stage of disease has not been clear. Therefore, this study investigated the predictive values of the pre-transformation standardized uptake value , interim (PETinterim) and end-of-induction therapy (PETend), respectively. Qualitative assessment was performed using the 5-point Deauville scale. Statistical analysis was done using Cox regression models, receiver operating characteristic (ROC) analysis, and Kaplan–Meir survival curves.This retrospective study involved 219 patients with FL between June 2008 and October 2019 who had undergone baseline and SUVend were significant predictors for HT, while neither SUVinterim nor qualitative assessment of Deauville score has predictive value for HT. Due to the noticeable impact of high pathological grade on the HT risk, we conducted the subgroup analysis in patients with low/high pathological grade, and found SUVbaseline could still predict HT risk in both low-grade and high-grade subgroups. Multivariate analysis adjusted by FLIPI2 score showed the SUVbaseline  and SUVend  remained as significant predictors independently of the FLIPI2 score. According to the cut-off determined from the ROC analysis, increased SUVbaseline with a cutoff value of 14.3 and higher SUVend with a cutoff value of 7.3 were highly predictive of a shorter time to HT.Of the 219 patients included, 128 had low-grade FL (grade 1–2) and 91 had high-grade FL (grade 3a). HT eventually occurred in 30 patients. The median time to HT was 13.6 months. Among clinical indicators, advance pathological grade was shown as the most significant predictor of HT . We further assessed the relationship between PET and HT risk in FL. Univariate Cox regression determined that SUVmax at the pre-treatment and end-of-treatment PET/CT scan may be helpful for early screen out patients at high risk of transformation and guide treatment decisions.In follicular lymphoma, quantitative assessment used SUVThe online version contains supplementary material available at 10.1186/s12935-021-02094-5. Follicular lymphoma (FL) is the most common form of inert non-Hodgkin's lymphoma (NHL), accounting for 7–15% of all lymphomas worldwide . Transfo18F-FDG PET/CT has been widely used in the clinic of lymphoma, including disease diagnosis, initial staging, and follow-up after treatment [max) derived from PET/CT is the most commonly used quantitative index as a standard of malignancy, and a higher value is generally considered a poor prognostic factor [max and total metabolic tumor volume (TMTV) parameters, and qualitative Deauville index are considered to be associated with inferior survival [max correlated with a worse PFS [max and the risk for HT in FL from the GALLIUM study, and found no temporal relationship between baseline SUVmax and HT; neither baseline SUVmax nor baseline SUVrange could predict HT [Over the past decade, reatment . The maxc factor . The Firc factor . In recesurvival –14, whilorse PFS . In termorse PFS . There aedict HT . Howevermax parameter and qualitative D5PS index of PET/CT evaluation at different treatment stages in predicting HT risk. Subgroup analysis was conducted in patients with low and high pathological grade, and the best cutoff values of PET/CT parameters were calculated as the basis for early screening and judgment of high-risk HT patients.To this end, in this study, we investigated the correlation between clinical indicators and HT risk, and further analyzed the quantitative SUVbaseline, PETinterim (after 3 or 4 cycles of chemotherapy), or PETend (after 5 or 6 cycles of chemotherapy) data were available. The treatment of low-grade (1–2) FL was decided by the hematooncologist depending on the patient’s condition. High-grade FL (3a) was treated with the following regimens: R-CHOP  and R-CVP . Nine individuals were excluded: two for whom pathologic grading data were lacking, two who showed lower FDG uptake in the tumor than in the liver at PET/CTbaseline, four who received radiotherapy due to a massive mass but did not receive chemotherapy, and one for whom time data for transformation were lacking. Clinical parameters and hematological data  level, fibrinogen, and subsequent treatment planned) were obtained from the patients’ medical records. The study was conducted per the ethical principles of the Declaration of Helsinki. All patients provided written informed consent to participate in the study .Two hundred and twenty-eight patients with histologically proven FL underwent PET/CT from June 2008 to October 2019. Among them, 219 patients who met the following inclusion criteria were included: patients having histologically confirmed FL with grading, including subsequent histologically confirmed transformation to other invasive lymphomas; patients having no evidence of biopsy-confirm transformation when underwent PET/CT scan; patients aged ≥ 18 years; and patients whose PET18F-FDG at 4.44–5.55 MBq/kg of body weight after at least 4–6 h of fasting. Adequate hydration was ensured by giving the patients 1000 ml of water 1 h before image acquisition. Blood glucose levels were checked in all patients before FDG injection. The patients’ blood glucose levels were lower than 11 mmol/L. Whole-body PET/CT scans were acquired using a combined PET/CT scanner . The whole-body CT and PET covered a region ranging from the meatus of the ear to the mid-thigh. PET/CT was performed approximately 1 h after FDG injection. The procedure for data acquisition was as follows: 16-section multi-detection row CT scanning was performed first, from the head to the mid-thigh with 120 kV and 100 mA. The tube rotation time and section thickness were 0.5 s and 5 mm, respectively, which matched the PET section thickness. Immediately after the CT scan, a whole-body PET scan was performed with 1.5- to 2-min acquisition per bed position by using a 3-dimensional acquisition mode. Attenuation-corrected PET images were reconstructed with an ordered-subset expectation maximization iterative reconstruction algorithm . PET, CT, and fused PET/CT images were generated and reviewed on a Syngo workstation. The scans were independently interpreted by two staff members of the PET center. Disagreements between respective independent interpretations were resolved by consensus.The patients received an intravenous injection of max was obtained by a software program from Siemens. The PETInterim and PETend scans were assessed using the D5PS as follows: 1, no intake; 2, intake less than or equal to that in the mediastinum; 3, intake higher than that in the mediastinum but less than that in the liver; 4, intake moderately higher than that in the liver; and 5, intake significantly higher than that in the liver or at a new disease site.The SUV refers to the ratio of the radioactivity of the imaging agent taken from local tissues to the average injection activity of the whole body. SUVContinuous variables were expressed as mean ± SD values. Estimates of the predictive effect for HT were expressed as hazard ratios (HRs) in the Cox proportional hazard regression analysis with 95% confidence intervals (CI). Receiver operating characteristic (ROC) analysis was performed to determine the optimal cut-off values for PET parameters for predicting HT. Transformation-free survival curves were constructed using the Kaplan–Meier method and were compared with the log-rank test. Differences between the results of comparative tests were considered significant if the 2-sided P-value was < 0.05. All statistical analyses were performed using STATA version 12.0 . The flowchart of the study protocol and methodology was shown in Fig. Of the 219 patients included (median follow-up: 46 months), 128 had low-grade FL (grade 1–2) and 91 had high-grade (grade 3a) FL. Thirty (13.7%) patients showed biopsy-confirmed HT to diffuse large B-cell lymphoma (DLBCL), with six cases (4.7%) categorized in the low-grade (1–2) group and 24 (26.4%) in the high-grade (3a) group. The median time to transformation was 13.6 months, and the earliest transformation was reported at 186 days (6 months). In the low-grade group, treatment was determined according to the Groupe d’Etude des Lymphomes Folliculaires (GELF) criteria for tumor load . Fifty-one (39.8%) patients adopted a watch-and-wait approach, 47 (36.7%) received involved site radiation therapy (ISRT) for a local mass, and only 30 (23.4%) received systemic chemotherapy. In the high-grade group, all included patients received chemotherapy, with 61 (67%) receiving R-CHOP and 30 (33%) receiving R-CVP. The median patient age was 51.1 years, and 47% of the patients were male. Table Univariate Cox regression was used to determine the baseline characteristics that could serve as predictors for HT. The results showed that older age, higher fibrinogen levels, higher FLIPI2 score, and advanced pathological grade were correlated with transformation (Table baseline), 64 received post-treatment interim evaluation , and 78 underwent post-treatment terminal evaluation . The median SUVbaseline was 8.1 , median SUVinterim was 2.9 , and median SUVend was 2.6 . SUVinterim and SUVend were assessed according to the Deauville scoring criteria, named as Deauvilleinterim and Deauvilleend, respectively. The PET/CT data for patients with HT and without HT are presented in Table baseline in patients with HT vs. without HT was 16.9 (range 2.12–29.72) vs. 7.9 (range 0.7–46.6), respectively; median SUVinterim was 2.49 (range 0–17.3) vs. 3.0 (range 0–11.4), respectively; and median SUVend was 7.3 (range 0–20.2) vs. 2.5 (range 0–15.5), respectively. The proportion of patients with higher qualitative assessment Deauvilleinterim (scored 5–6 points) was 25% (2/8) and 10.9% (6/55) in the HT and non-HT groups, respectively; the percentage of patients classified as higher at Deauvilleend (scored 5–6 points) was 50% (3/6) and 14.2% (10/70) in the HT and non-HT groups, respectively.Univariate Cox regression analysis showed that the SUVbaseline  and SUVend  could predict HT. Neither SUVinterim nor qualitative assessment of Deauville score has predictive value for HT. A total of 128 patients with pathological grade 1–2 received multiple mild treatments and 91 patients with pathological grade 3a received rituximab-based systemic chemotherapy. To minimize the confounding effects of pathological classification and treatment strategies on the results, we conducted subgroup analysis in low (grade 1–2) and high (grade 3a) pathological grade patients, respectively. The result showed the baseline SUVmax was still an important predictor for HT in both high-grade  and low-grade subgroups ; SUVend also remained as a prognostic indicator for HT in high-grade subgroup . Due to the insufficient sample size, statistical data on predictive value of SUVend in low-grade subgroup could not be obtained. In addition, we conducted a multivariate Cox analysis of adjusted by FLIPI2 score on the significant indicators screened by univariate analysis, and found the SUVbaseline  and SUVend  remained predictive factors of HT risk independently of FLIPI2 score.Among the 219 patients with PET/CT data, 132 underwent pre-treatment PET/CT evaluation   for SUVFollicular lymphoma shows a heterogeneous clinical course ranging from long-term responses to initial therapy to frequent recurrences or transformation to more aggressive subtypes. Histological transformation is a serious clinical event with a marked effect on the disease outcomes. In the past few decades, the incidence of HT has been reported to vary from 10 to 70% , 18–22. Even though in rituximab era, HT is still a serious event affecting the prognosis and survival of follicular lymphoma, especially in patients with subsequent transformation, with a 5-year PFS rate of less than 20% and 5-year OS rate of less than 70% . The tramax reflects the glucose metabolism of tumors, and has been proved to be closely related to tumor invasion [max > 14.5 was associated with poorer PFS than baseline SUVmax ≤ 14.5 [end and found that a high TMTV (> 510 cm3) and positive PETend results were independent important risk factors for PFS [Recently, some studies have investigated the potential predictive value of quantitative parameters of PET/CT for FL prognosis. As the most commonly used semi-quantitative indicator in PET/CT, SUVinvasion , 29, 30.x ≤ 14.5 . With thx ≤ 14.5 . Cotteremax than non-transformed sites on PET/CT scans. Numerous studies have confirmed that higher SUVmax values increase the odds of higher grade or more aggressive lymphoma, and PET/CT is often used as an important non-invasive diagnostic tool to find the best biopsy site when transformation is suspected [max and the risk for HT in FL from the GALLIUM study [max and HT. Neither baseline SUVmax nor baseline SUVrange could predict HT, suggesting that repeat biopsy of lesions may offer limited benefit in excluding HT based on SUVmax alone before initiating therapy in patients with FL with a high tumor burden. This study highlighted for the first time the insignificance of baseline SUVmax in predicting transformation risk, but the limited sample size (only 15 patients with HT) and a single population (patients with high tumor burden) may lead bias in results. Moreover, the usefulness of mid-term and terminal PET/CT assessments in predicting HT has not been reported to date. Therefore, we retrospectively collected a decade data to analyze the predictive power of pre-transformation PET/CT for the risk of HT in FL. All patients had no evidence of histological transformation when underwent PET/CT scans.In term of relationship between PET/CT and HT in FL, retrospective studies showed that the nodal sites of HT may have a higher SUVuspected . To dateUM study . They fomax both indicated a shorter time to HT. While in visual analysis, the results of the interim or post-treatment Deauville 5-point scale assessment, which uses liver activity as the reference, were not associated with the time to HT in FL. In our study, grade 3a disease was found to be the most important factor affecting transformation, and treatments containing rituximab have been reported to be closely related to a reduced incidence of transformation. Here, the treatment protocols for patients with grade 3a disease (R-CHOP or R-CVP) were more uniform than those for low-grade patients. To minimize the confounding effects of pathological classification and treatment strategy, we analyzed the predictive ability of PET/CT parameters for HT in low-grade and high-grade subgroups, respectively. The results showed the SUV baseline was still an important predictor for HT in both high-grade and low-grade subgroups. SUVend also remained as a prognostic indicator for HT in high-grade subgroup. These findings imply that a higher baseline SUVmax represents higher tumor invasiveness, leading to a higher probability of subsequent transformation, and poor efficacy of induction therapy is also an important factor influencing transformation. The NCCN-FLIPI2 was proposed recently and proved more accurate for identifying high-risk patients in the era of immune-chemotherapy. In our study, the NCCN-FLIPI2 score was also shown to be highly predictive for patients at risk of transformation. Therefore, we used multivariate analysis to evaluate the prognostic values adjusted by NCCN- FLIPI2 score, and concluded that SUVbaseline and SUVend were significant HT predictors independent of NCCN- FLIPI2 score.Our result showed that in quantitative assessments, higher levels of initial and post-treatment SUVRecently, cytogenetics and tumor microenvironment to predict HT have also been studied. No single gene lesion could explain all cases of HT. TP53 mutation, loss of CKDN2A, and gains of MYC were reported to be participated in development of HT . The micmax may not be suitable for biopsy, and the possibility of de novo transformation cannot be completely ruled out.Our study has several limitations. First, the study design was retrospective. Second, although the study included 219 patients, the PET/CT dataset provided was insufficient. The PET/CT data for the pre-treatment phase, interim period, and the end of treatment were obtained from scattered patients, and data for all three stages were available for very few individual patients. The lack of parallel data of patients and insufficient data for analysis reduced the reliability of the conclusion. In addition, although the initial biopsy-confirmed HT did not occur, sites with a high SUVbaseline and SUVend were validated to show predictive value on HT risk independently of FLIPI2 score, and may help to identify high risk patients in clinical. Given the bias caused by the analysis of scattered data in this study, more prospective studies with larger samples are needed to confirm the predictive ability of pre-trasformation PET/CT and whether patients could benefit from a change in treatment strategy based on PET/CT-based risk stratification of HT.Although HT occurs in a minority of patients with follicular lymphoma, it significantly worsens the survival, prompting the clinical significance of early screening of high-risk HT patients. The biology of HT is complex, no single genetic lesion or mechanism could explain all cases of HT, and no clinical indicators or biomarks to strongly predict HT have been identified to date. PET/CT is used as a non-invasive diagnosis tool to help determine the best biopsy site when suspecting HT, but its role in predicting the HT risk in the early stage of disease is still unclear. The present study provides a decade of retrospective data to analyze the relationship between HT risk and PET/CT parameters at the initial, interim and end-treatment stages. SUVAdditional file 1. The original data.


The efficiency of the developed C-dots was also investigated in the presence of various other amino acids and different water mediums in order to enhance the working scope of the developed sensors.In the recent era, carbon dots (C-dots) have been extensively considered as a potential tool in drug delivery analysis. However, there have been fewer reports in the literature on their application in the sensing of amino acids. As part of our ongoing research on coconut-husk-derived C-dots, we synthesized C-dots under different temperature conditions and utilized them in the field of amino acid sensing and found them to be highly selective and sensitive towards tyrosine. The detailed characterization of the prepared C-dots was carried out. The developed C-dots exhibit good values of quantum yield. BSA, HSA and glutamic acid were utilized to explore the binding efficiency of C-dots with biologically active components. Hemolysis, blood clotting index activity and cell viability assays using the prepared C-dots were evaluated and they were found to be biocompatible. Therefore, the C-dots described in this work have high potential to be utilized in the field of amino acid sensing, especially L-tyrosine. The limit of detection and the binding constant for the developed C-dots in the presence of tyrosine were found to be 0.96 nM and 296.38 nM As on2) . The catus media . HoweverIn this regard, carbon dots have shown significant potential in providing a ratiometric fluorescence response towards low concentrations of analytes in aqueous media ,18,19,20Inspired by the promising scope of applications of carbon dots, we aimed to fabricate a highly selective and sensitive fluorescent probe with carbon dots for the detection of L-tyrosine. The carbon dots were synthesized through the single-step thermal calcination of coconut husk as the precursor source and referred to as “C-dots”. As one of the most important oilseed crops, coconut production has been significantly rising annually ,31,32. IThe current work offers an effective and alternative means to convert coconut husk waste into highly fluorescent C-dots for label-free fluorescent probes targeting L-tyrosine. The current work fills the gap in our knowledge on the available experimental research involved in converting coconut husks into C-dots. The information gaps regarding the effect of thermal calcination temperatures on the conversion of coconut husks to C-dots and its consequences in regard to the size, shape, morphology, optical and luminescence properties during the formation of C-dots have been thoroughly investigated in this work. Additionally, the binding efficiency of formed C-dots with BSA, HSA and glutamic acid has been investigated to verify the biocompatibility of the formed particles. The hemolysis and blood clotting index activity of the prepared C-dots were evaluated and their cell viability was examined through the MTT assay. The current work offers the possibility to future researchers of converting waste biomass to highly advanced, biocompatible, and selective fluorophores. Furthermore, the prepared C-dots provide a “turn-off” sensor probe and have the potential for use in intracellular imaging for the detection of L-tyrosine by using highly biocompatible and non-lethal C-dots.42−, Cl−, SO32−, NO32−, NO2−, SO42−, CO32−, HCO4−, and S2O82−) of barium salt were purchased from Avra chemicals, Hyderabad, India with 98% purity. Deionized water was utilized during all experimental procedures for the preparation of samples. 3--2,5-diphenyl tetrazolium bromide (MTT) and 2’,7’-dichlorodihydrofluorescein diacetate (DCFH-DA) were purchased from Sigma-Aldrich, Bangalore, India. Murine macrophage cell lines (RAW 264.7) were purchased from the National Centre for Cell Science (NCCS), Pune, India. The cells were maintained in DMEM, supplemented with 10% fetal bovine serum (FBS), 100 mg/L streptomycin, and 100 IU/mL penicillin, at 37 °C in a 5% CO2 incubator. All the samples were used without any further purification.The lyophilized powder form of bioreagent-grade bovine serum albumin (BSA) and human serum albumin (HSA) were procured from Sigma-Aldrich, Bangalore, India, with purity <98%. Phosphate buffer with pH 7.4 was prepared in a laboratory by mixing sodium phosphate dibasic and sodium phosphate monobasic. Both sodium phosphate salts were purchased in anhydrous form with 99% purity from Sigma-Aldrich. Twenty amino acids  were purchased from Sigma-Aldrich, Bangalore, India with 99% purity. Inorganic anions  with a heating plate. A Jasco V-750 UV-vis. spectrophotometer  was used to evaluate the absorption behavior of C-dots in a quartz cuvette in a fixed path length of 1.0 cm and a working range of 200–800 nm. Furthermore, the emission profile was assessed by employing a Perkin Elmer LS 55 spectrofluorometric instrument  in a working range of 200–800 nm and average scan range of 500 nm. The hydrodynamic size distribution and polydispersity index of the formed C-dots were checked on a MALVERN ZEN 1690 dynamic light scattering (DLS) instrument . The existence of different kinds of functional groups over the exterior surfaces of the formed C-dots were checked using Perkin Elmer (RXI) Fourier transform infrared (FTIR) spectroscopy  in a working range from 500 to 4000 cm−1. The purity, morphological changes, and elemental mapping of the formed C-dots were tested on a field emission-scanning electron microscopy (FE-SEM) instrument  with an energy dispersive X-ray spectroscopy (EDX) unit at 20 KeV. Simultaneously, the direct imaging and their distribution profile was assessed on a high-resolution transmission electron microscope (HRTEM) H-7500 from Hitachi  at 100 kV. The crystalline behavior of the developed C-dots was verified using a Panalytical X’Pert Pro powder X-ray diffractometer  with monochromatic CuKα radiation between angles of 5°–90° and an average scan range of 2 deg/min. The crystalline size was calculated by using the Debye Scherrer formula D = Kλ/βCosθ, where K corresponds to a dimensionless shape factor of which the value is taken as unity (0.94), λ refers to the X-ray wavelength with a value of 0.154 nm, β corresponds to the full width at half maxima (FWHM) intensity and θ corresponds to Bragg’s angle calculated based on XRD data. The effect of pH (acidic and basic conditions) on the surface properties of the developed C-dots were investigated using a Mettler Toledo digital pH meter. The thermal characteristic behavior of the formed C-dots was inspected using an SDT Q-600 thermo-gravimetric analytical differential scanning calorimeter (TGA-DSC) instrument under nitrogen atmosphere in a working range of 0–1000 °C and a Mettler Toledo Q20 instrument  in a working range of 0–350 °C, respectively. The zeta-potential values of pure C-dots and in the presence of different types of biological components were inspected on an Anton Paar Litesizer 500 instrument  with Omega measurement cells.The thermal insulating environment was provided by a AICIL muffle furnace during the synthesis of C-dots. The purification of C-dots was performed on a Remi R-24 centrifuge at 5000× The quantum yield (Φ) value is considered one of the significant parameters in the case of active fluorescent nanodots. It is defined as the number of photons emitted, divided by the number of photons absorbed by the system. Its value directly depends upon the chemical structure and environment of the developed fluorescent system. During fluorescence spectroscopy, it has been observed that after molecules absorb photons, they do not always emit the same number of photons because of non-radiative relaxation from the excited state to the ground state, which leads to a quantum yield value <1 (100%). Here, tyrosine and tryptophan were utilized as reference standards (Φ = 0.14 and 0.13) for the calculation of the quantum yield of prepared C-dots under different temperature conditions. For this analysis, an aqueous solution of each respective amino acid was prepared and its absorption and emission analyses were carried out. The formula mentioned below was used for the calculation of quantum yield:spectrum ,40,41,42To investigate the photochemical stability of the prepared C-dots in aqueous medium, a time replication study was carried out. For the respective study, a fixed concentration (2 mg in 5 mL) of C-dots was kept for different intervals of time and their fluorescence spectra were recorded in working range of 200–800 nm.The influence of pH on the synthesized C-dots was also tested by recording the fluorescence behavior of the formed samples with different pH values at room temperature. For this analysis, six different pH solutions  of C-dots were prepared using dilute HCl and NaOH solutions and their fluorescence spectra were recorded in the range of 200 to 800 nm.The respective salt effect activity was analyzed to obtain information about the ionic strength of the C-dots in the presence of different ions. Their emission behavior in the presence of different salts was assessed using fluorescence spectrophotometric measurements. Solutions of NaCl and KCl with different concentration ranges of 0 mM, 100 mM, 250 mM, and 500 mM were prepared in deionized water and their emission behavior was tested using fluorescence spectroscopy in the range of 200 to 800 nm.The UV-vis. spectroscopic measurements were carried out in order to investigate the binding capacity of the formed C-dots with BSA, HSA and glutamic acid. The 0.2 M phosphate buffer solution was chosen as the reference sample during UV-vis analysis. The sample of C-dots with different concentrations ranging from 2 mg to 9 mg in 5 mL were prepared in 0.2 M phosphate buffer solution (pH = 7.4) for the analysis. During the measurements, the concentration of BSA was fixed at 1.25 mg per mL of solution. Similarly, the concentration of HSA protein and glutamic acid was kept at 1.0 mg per ml of solution. The stock solutions of all the biological components were prepared in 0.2 M phosphate buffer. The electrical charge and stability of developed system was checked using zeta potential measurements .g and the supernatant was collected and their absorbance values were measured at 540 nm to evaluate the released amount of hemoglobin. Further, to test the blood clotting index of the prepared C-dots, 0.2 M CaCl2 solution was gradually assorted with the freshly collected blood samples to prevent the rupturing of blood plasma. Subsequently, 0.5 mL of differently concentrated solutions of C-dots was allowed to mix with the fresh blood suspension and incubated at room temperature for 15 min. Afterwards, 3 mL deionized water was added to the above prepared samples and centrifuged at 1000× g for 4 min and supernatant collected from the respective solutions was diluted further by adding deionized water and was again incubated at 37 °C for 10 min. The absorbance value for each sample was recorded at 542 nm. The values of the blood clotting index and hemolysis ratio were calculated using the following equations:The hemolysis assay provides information about the damage to erythrocytes in the presence of external moieties. For this analysis, fresh blood samples from a volunteer were procured in EDTA-coated vials to explore the hemolysis and blood clotting index of the developed C-dots. The reduction of the concentration in freshly acquired blood samples (human erythrocytes) was measured using 1% saline solution in the presence of different concentration levels (2 to 9 mg/mL) of C-dots. Known and equal volumes of C-dots mixed with 0.2 mL of diluted blood samples were prepared in suspension form and allowed to incubate at 37 °C for 50 min. The respective solutions were centrifuged using physiological saline solution for 4 min at 1000× Here, OD corresponds to the optical density (absorbance) values, subscript positive indicates a sample diluted with water, and negative refers to a blood sample diluted with the saline solution ,45.4 cells/mL, were seeded into a 96-well culture plate, and left overnight for incubation. After attachment, the cells were treated with different concentrations of the C-dots and incubated for another 24 h. The media containing C-dots were removed and MTT (25 µL of 5 mg/mL) was added to the wells and kept for 4 h at 37 °C in the incubator. After removing the supernatant, the formazan crystals formed were dissolved in 100 µL DMSO. The absorbance of the resultant solution was read at 570 nm using a microplate reader (BioRad). The percentage of viability of the cells was calculated asThe reduction of yellow 3--2,5-diphenyl tetrazolium bromide (MTT) by mitochondrial succinate dehydrogenase to an insoluble purple-colored formazan product is the basis of the MTT cytotoxicity assay . The forp < 0.05.Intracellular ROS generation/scavenging after treating the cells with C-dots was measured via the 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA) fluorescent staining assay. RAW macrophages grown to confluency were treated with different concentrations of C-dots at 37 °C for 24 h in an incubator. The media containing C-dots were removed and 500 μL of DCFH (10 μM) solution (prepared immediately before the experiment) was added to the wells. The cells were incubated for 30 min. DCFH-DA is a non-fluorescent dye and shows fluorescence in its reduced state when the acetate groups are removed using intracellular esterase to produce green fluorescence . The greOne-micromole solutions with concentrations of the chosen amino acids were prepared by sonicating the prepared samples for 30 min. Around 2 mg of powdered C-dots was suspended in 5 mL of deionized water and allowed to sonicate, forming a homogenous dispersion, then was left undisturbed for 30 min at room temperature under optimal conditions. Afterwards, a 1 mL solution of the prepared amino acid solution was allowed to mix with an equal volume of C-dots. The fluorescence spectrum for each prepared sample was recorded in a working range of 200 to 800 nm. Upon interpreting the results, it was observed that the formed C-dots were quite selective and sensitive for tyrosine.After observing the selectivity of tyrosine of the formed C-dots, studies of their concentration variations were performed in terms of a titration scheme using fluorescence spectro-photometric measurements. For analysis, the concentration of tyrosine was varied from 100 nM to 1 nM and their detection limit values were calculated.0 vs. concentration) by applying the formula: The values of the detection limit (σ) and quantitation limit (β) were calculated using a Stern–Volmer plot (F/Fids used .0 vs. conc.) was drawn between emission intensity and the reciprocal of the tyrosine concentration in order to estimate the binding efficiency and stoichiometry of the C-dots with tyrosine amino acid using the following equation:A Benesi–Hilderbrand plot  through fluorescence spectroscopy. For the respective activity, 1 mL of the C-dot suspension was mixed with 1 mL of tyrosine. The sample preparation of Tyrosine with different concentration levels  was carried out in different real wastewater media. The emission profiles of the respective samples were analyzed in a working range of 200–800 nm. All the experimentation were carried out in triplicate in order to scrutinize the applicability of the respective system ,25.1 was associated with the π-π* transition in the C=C bond present as the structural unit in the C-dots  and O-H (hydroxyl) functionality over the exterior surface of the formed particles. In addition, variation in the calcination temperature during the fabrication of the C-dots produced significant shifts in the absorption peaks. This behavioral variation can be explained due to the enhancement in the local refractive index of the surroundings of the formed C-dots. In addition, fluorescence spectroscopy was used to explore the emission behavior of the formed C-dots in the range of 200–800 nm. They display a bright fluorescent blue color under UV illumination. The quantum yield values CD1, CD2, and CD3 were calculated respectively  utilizing tyrosine and tryptophan standard dye (λex. = 280 nm) as a reference material , (002), (100), (100), (102), (101), (110), and (200). In the case of CD2 and CD3, the diffracting plane was observed at 2θ = 28.26°, 33.83°, 40.45°, 50.36°, and 66.43°, corresponding to (002), (111), (100), (101), and (200). The calculated crystalline sizes of CD1, CD2 and CD3 were 90.43, 62.91, and 51.67 nm, and the dislocation density values were 12.22, 25.26, and 37.45 (10−5) nm−1, respectively. From these results, it can be concluded that the developed C-dots were completely synthesized in the nanometric range and displayed the well-developed diffraction peaks of carbon dots. The nature of the different types of functional groups on the surface of the C-dots was evaluated through FTIR analysis  in the range of 200–500 nm. The absorbance band at 210 nm in the case of CDe C-dots a. In thematerial . This wamaterial . The C-dectively b. The crectively c. In theanalysis d. In casibration ,21. C=C 1 and CD2, with average sizes of 42 and 28 nm. However, the spherical morphology of CD3, with an average size range of 12 nm, is clearly visible in the FESEM images  were considered to be the most appropriate for carrying out further analysis due to their small size, better thermal properties, and excellent absorption and emission properties. They were further utilized in the application of biological component sensing.FESEM and HRTEM techniques were utilized to analyze the morphological and topographical symmetry of the developed C-dots. The FESEM analysis of the dried powdered C-dots was carried out to evaluate their morphological behavior in their dried form. Based on the FESEM images ai–ci, itM images ci. In adM images aii–cii.  0.25 nm cii. Thes 0.25 nm . Further 0.25 nm . Based o1, weight losses of 17.69%, 29.48%, and 58.79% were observed at 195 °C, 598 °C, and 985 °C, respectively. In the case of CD2, weight losses of 8.94%, 15.54%, and 52.64% occurred at 198 °C, 595 °C, and 995 °C. However, for CD3, 17.69%, 18.28%, and 70.92% weight losses were observed at 192 °C, 593 °C, and 987 °C, respectively. The first weight loss was mainly due to the evaporation of water molecules and the moisture content in the sample. The second weight loss corresponded to the evaporation of pyro gases  present on the surfaces of the C-dots. The third weight loss corresponded to the evaporation of different functional groups  present on the exterior cores of the C-dots. Further DSC analysis was carried out for the developed C-dots to explore their exothermic and endothermic behavior in the form of a heat release. The value of the onset temperature (To), glass transition temperature (Tg), melting temperature (Tm), and heat of enthalpy and entropy was calculated for all the prepared types of C-dots  were analyzed under different pH, ionic strength, and time conditions. For this analysis, the emission intensity of the formed C-dots was investigated by varying the pH values from 2 to 13  into the protein solution significantly enhanced the value of the optical density. However, the optical density upsurged linearly when increasing the amount from 2 mg to 9 mg. The augmentation in the absorbance values of protein molecules in the presence of C-dots arose due to the variation in the microenvironment of the protein molecules. There was no significant shift in the peak positions of the chosen proteins in the presence of C-dots. These results suggested stable ground-state-complex formation between the proteins and C-dots. The well-organized and closed structure of the peptide bonds in proteins changed to an insecurely and loosely bound scrambled structure, due to the absorption of C-dots on the surface of proteins. The obtained zeta potentials of −12.8, −18.7, and −6.39 eV for BSA, has, and glutamic acid suggested the electrical charge stability of the protein molecules  with the prepared C-dots provided valuable information about their quenching and binding ability. Among the different spectroscopic methods, the current study utilized the sensitivity of UV-vis. spectroscopy to study the electrostatic interaction mechanism of proteins and the prepared C-dots. The spectra displayed characteristic peaks at 275, 280, and 205 nm for BSA, has, and glutamic acid . In the ansition a,b, wherion peak c. The orolecules . The negThe biocongenial performance of the highly stable prepared C-dots was also evaluated by assesssing out the hemolysis and blood clotting index activity at different concentrations (2–9 mg/mL). The adapted in vitro stability activity will provide a new pathway for the use of the developed C-dots in biological applications. The concentration variation behavior of the C-dots will provide a significant influential effect on blood systems d. It wasThe effect of the C-dots on the growth of macrophages was studied by treating the cells with developed particles at different concentrations and incubating the cells for 24 h. The viability of cells was assessed using an MTT assay. The slight growth inhibition was obvious in the presence of C-dots. It was found that 1 µg/mL of the C-dots was able to decrease the growth of the tested cell lines close to 32% a. This i2 and PLGA-PEO NPs also showed a decrease in the emission of DCFH-DA probe fluorescence [As shown in rescence , which c−) and (NH3+), respectively. The most important feature of tyrosine amino acid is the presence of a phenolic group which possess extreme charge transfer characteristics with the developed C-dots. The hydroxyl group of the phenol moiety causes a major charge transfer process, which suggests the outstanding sensitivity of tyrosine towards C-dots. Therefore, stable ionic complex formation occurred on both sides and was quite high in L-tyrosine. The hydrogen bonding between the different functional groups present on the exterior surface of the C-dots also suggested an interaction with L-tyrosine. The close proximity of hydrogen binding can lead to a quenching effect on the fluorescence intensity of the C-dots  scheme [Twenty amino acids  were utilized to certify the selectivity of the prepared C-dots a. Fluoree C-dots b. The sl) scheme ,49. The −, Br−, OH−, NO2−, NO3−, SO42−, CO32−, AcO−, S2O32−, and SO32−) and biomolecules . The interfering mechanism was considered active only when the analytical discrepancy was >30% as compared to the signal obtained during the proposed analysis due to the absence of interfering ions. However, the obtained interfering results indicated that no additional interference was obtained for the analyte in the presence of different ionic species (0 vs. conc. of tyrosine) and Benesi–Hildebrand plot (1/F − F0 vs. 1/conc. of tyrosine)  . The valThe developed C-dots reflected ultimate selectivity and sensitivity towards L-tyrosine. Therefore, its practical analytical performance was evaluated in the presence of real water samples taken from four different sources viz. lake water, rainwater, tap water, and well water . The resIn this paper, fluorescent C-dots were prepared usingcoconut coir waste as a precursor material. The developed scheme for the synthesis of C-dots can be carried out easily and reflects excellent selectivity and stability. Different analytical methods were employed to analyze the characteristic behavior of the C-dots. It was observed that the developed C-dots were completely synthesized in the nonorange with available functional groups. Furthermore, various biological activities were assessed in the developed C-dots to evaluate their biocompatible and non-toxic behavior. The cell viability of the developed C-dots was investigated using an MTT assay. The obtained results suggest the non-toxic behavior of the C-dots. The developed tyrosine-sensing ability leads to miniaturization of highly expensive instrumentation. The developed scheme was successfully utilized and applied for the detection of tyrosine among various amino acids in different water samples with satisfactory recovery values. The value of the detection limit was found to be 0.96 nM. From these results, it can be concluded that the developed C-dots can be utilized in the field of biological component sensing, with appropriate selectivity and sensitivity at low concentration levels.


Brachypodium hybridum (genome composition DDSS), which is a polyphyletic species that arose from crosses between two putative ancestors that resembled the modern B. distachyon (DD) and B. stacei (SS). In this work, we investigated the developmental stability of ND in B. hybridum genotype 3-7-2 and compared it with the reference genotype ABR113. We addressed the question of whether the ND is established in generative tissues such as pollen mother cells (PMC). We examined condensation of rDNA chromatin by fluorescence in situ hybridization employing state-of-art confocal microscopy. The transcription of rDNA homeologs was determined by reverse-transcription cleaved amplified polymorphic sequence analysis. In ABR113, the ND was stable in all tissues analyzed . In contrast, the 3-7-2 individuals showed a strong upregulation of the S-genome units in adventitious roots but not in other tissues. Microscopic analysis of the 3-7-2 PMCs revealed extensive decondensation of the D-genome loci and their association with the nucleolus in meiosis. As opposed, the S-genome loci were always highly condensed and localized outside the nucleolus. These results indicate that genotype-specific loss of ND in B. hybridum occurs probably after fertilization during developmental processes. This finding supports our view that B. hybridum is an attractive model to study ND in grasses.Nucleolar dominance (ND) is an epigenetic, developmentally regulated phenomenon that describes the selective inactivation of 35S rDNA loci derived from one progenitor of a hybrid or allopolyploid. The presence of ND was documented in an allotetraploid grass,  Allopolyploidy is an interspecific hybridization followed by chromosome doubling and it is believed to play an essential role in angiosperm evolution . The genCrepis hybrids. In the allopolyploids and hybrids that exhibit ND, the 35S rDNA loci that are inherited from one progenitor are dominant over the others , a widespread phenomenon that was initially documented by e others . It is we others  and are e others . Moreovee others  and the e others . HoweverTriticum aestivum L.)  in which many 35S rDNA loci are present, studies of ND in this species are tremendously complicated. Thus, it is necessary to find a monocot model system that will be amenable in ND studies.Nucleolar dominance is a common phenomenon among grass allopolyploids, including the economically important cereals, e.g., bread wheat (ivum L.)  and tritivum L.) . Therefoivum L.) , which iBrachypodium hybridum . Its putative ancestral species are two diploids that resembled the modern B. distachyon  and B. stacei . It was documented using silver staining followed by fluorescence in situ hybridization (FISH) with 25S rDNA as the probe that the S-genome-derived 35S rDNA loci are not transcribed in the root-tip meristematic cells  was obtained from the Institute of Biological, Environmental and Rural Sciences . The 3-7-2 genotype was derived from the T1 generation of the germplasm that had been collected in Turkey . All of the plants were grown in pots with soil mixed with vermiculite  at 20–22°C and a 16 h photoperiod in a greenhouse.Two genotypes of To analyze mitotic metaphase chromosomes from the primary roots, dehusked seeds were grown on a filter paper that had been moistened with tap water for 3 days at room temperature in the dark. Whole seedlings with 1.5-3-cm-long roots were immersed in ice-cold water for 24 h and then fixed in methanol:glacial acetic acid  at 4°C overnight and stored at −20°C. Immature spikes for the analysis of the meiocytes were collected from 2 to 2.5-month-old plants, fixed in fresh ethanol:glacial acetic acid  at room temperature. The fixative was replaced by a fresh one after 24 h. The material was stored at −20°C until use.B. hybridum were isolated using a CTAB buffer as described previously (BglII restriction enzyme cutting the AGATCT motif. The digested gDNAs were separated by gel electrophoresis on 1% (w/v) agarose gel and alkali-blotted onto nylon membranes . The membranes were hybridized with 32P-labeled DNA probes  using the ∼220 bp-long PCR product derived from the 3′ end of the 25S rDNA of tobacco as previously described (B. distachyon-specific band) or 7.8 kb + 9.2 kb (B. stacei-specific bands) fractions out of the total (6.7 kb + 7.8 kb + 9.2 kb) rDNA signal. At least two individuals  from each B. hybridum genotype were analyzed.Total genomic DNAs (gDNAs) from the leaves from 1.5-month-old plants of eviously . The purescribed . The hybClaI subclone of the 25S rDNA of A. thaliana (via nick translation (in situ hybridization (FISH) was performed as previously described . Three different individuals  have been analyzed for both primary and adventitious roots. Only the metaphases with visible secondary constrictions on the D-genome chromosomes have been considered (15–26 metaphases/meristem). In the case of interphase nuclei, approx. 100 nuclei have been analyzed for each individual.The root meristem cytogenetic preparations, including the multi-substrate preparations, were made as described . A 2.3-kthaliana  was usednslation . Fluoresescribed . After pB. hybridum were embedded in acrylamide gel to preserve their three-dimensional architecture. The procedure of embedding was adopted from The meiocytes of –1 DAPI, 200 mM Tris-HCl pH 8, 2.3% DABCO octane) and 78% glycerol] and stored at 4°C until the images were acquired.FISH on the polyacrylamide pads was performed as was described in Images of the mitotic metaphase chromosomes after FISH were acquired using a Zeiss Axio Imager.Z.2 wide-field fluorescence microscope equipped with an AxioCam HRm monochromatic camera. The meiocytes that had been embedded in the polyacrylamide gel were optically sectioned using an Olympus FV1000 confocal microscope system equipped with a 60×/1.35 PlanApo objective. All of the image stacks were acquired by scanning from the top to the bottom of a meiocyte in 0.25 μm steps and then processed using MBF ImageJ .® RNA Plant and Fungi kit (Macherey-Nagel). Any contaminating DNA was removed using an RNase-Free DNase set (Qiagen). Each reverse transcription reaction contained 1 μg of total RNA and 1 μl of Maxima H Minus Enzyme Mix (Thermo Fisher Scientific) and was performed according to the manufacturer’s instructions. The obtained cDNAs were used as templates in the ITS1 amplification using PCR with the primers 18S and 5.8S rev  a fast-migrating, 6.7-kb-long fragment representing the D-genome rDNA units; (ii) 7.9-kb-long fragment representing the S-genome rDNA units in which both BglII sites were cut by the enzyme; and (iii) a slow-migrating fragment representing the full-size S-genome rDNA unit. The radioactivity of the hybridization bands was estimated by a phosphorimager revealing the quantitative relationships between the ancestral rDNAs  and the generative organs . Because of the ITS1 sequence divergence between the two ancestral species, the rRNA precursors (pre-rRNA) that originated from the D- and S-genome 35S rDNA loci could be identified. The MluI enzyme only cuts the B. distachyon-like units producing two fragments  approach was used to examine the expression of the 35S rDNA homeologs at the different developmental stages of ragments . Becausere uncut . In ABR1al rDNAs . The low35S rDNA .Arabidopsis suecica, the progressive silencing of the A. thaliana-originated rRNA genes occurred during the early postembryonic development in the tissues that had been derived from both the shoot and root apical meristems  the localization of both ancestral homeologs in the meiocytes that had been isolated from the anthers and (ii) the origin of the pre-rRNA in the immature spikes. The FISH with 25S rDNA as the probe was performed on the B. hybridum 3-7-2 meiocytes at different substages of prophase I and in the dyads. Only one nucleolus per cell was observed in all of the studied stages of meiosis (B. stacei-inherited loci were located at the nuclear periphery in the DAPI-positive domains (B. hybridum 3-7-2 (Arabidopsis thaliana, whose all loci, irrespective of activity, seem to associate with the nucleolus in meiosis (The reprogramming of the rRNA gene expression may accompany the transition from the vegetative to the generative phase as was shown in Brassica  and Solalyploids . To veri meiosis –5. At th meiosis , while t domains . Beginni domains –4. Moreo domains . RT-CAPSum 3-7-2 . Thus, N meiosis . Thus, iB. napus. They observed the reactivation of the B. oleracea-inherited rDNA loci in all of the floral organs, including the sepals, petals, anthers, and siliques. Thus, the hypothesis that a derepression of the under-dominant rRNA genes occurs when both ancestral rDNA homeologs are segregated by meiosis as was shown previously in triticale (B. napus showed only a trace expression of the B. oleracea-derived rDNA in the flower buds of two of the seven studied cultivars. These observations indicated that the ND regulation might even be genotype-specific. Such a specificity of the ND regulation among the floral organs in B. hybridum has not been observed yet. In addition to the current study on genotype 3-7-2, the ND establishment in the meiocytes was only analyzed in the reference genotype ABR113 (The studies of riticale  may not riticale . The fure ABR113 . The S-ge ABR113 .B. hybridum genotype with a co-dominance of the D- and S-genome rDNA homeologs in the primary and adventitious roots. B. hybridum 3-7-2 and shows the developmental regulation of ND in this species. Further comparative studies of the rDNA molecular structure in B. hybridum may shed more light on the specific mechanisms that shape ND in grasses. There is some evidence that both the chromosomal position and/or the presence of the control elements that are located within rDNA units may be responsible for the preferential expression of rDNA via ND (To the best of our knowledge, this study revealed the first A via ND . Thus, uA via ND  may signThe original contributions presented in the study are included in the article/NB-Z conceived and designed the study. NB-Z, ER, SM, JW, AP, and AK performed the experiments. NB-Z, ER, AK, and RH analyzed the data. NB-Z and RH wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.